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This paper aims to explore the design of management teams when the critical task facing individual managers is monitoring the performance of worker teams and producing performance measures under uncertain information environments.

The authors use a multi-agent LEN framework – linear contract, exponential utility and normal density – to model the incentive provision and organizational design.

The main lesson is that the use of performance measures under uncertainty is greatly affected by the potential for free-riding in the very monitoring activities which generate the measures to begin with. Accordingly, the value of having a management team, that is the incremental benefit of having a second manager, depends on the monitoring technology. Of particular importance are the potential free-riding in monitoring effort among multiple managers and synergies gained from having more than one manager, such as correlation among the performance measures produced or improvement due to splitting workers pool into separate groups for each manager to monitor separately.

The paper pushes this line of research further by explicitly modeling the endogenous process of signal generation within a rich economic environment. In this environment, number of workers being evaluated and number of managers who produce the signals are both endogenous. Furthermore, both workers and managers are subject to moral hazard problem. In particular, the managers suffer from potential free-riding problems but may benefit from synergistic forces due to team monitoring.

This paper aims to analyse how emerging technologies (ETs) impact on improving performance in disaster management (DM) processes and, concretely, their impact on the performance according to the different phases of the DM cycle (preparedness, response, recovery and mitigation).

The methodology is based on a systematic review of the literature. Scopus, ProQuest, EBSCO and Web of Science were used as data sources, and an initial sample of 373 scientific articles was collected. After abstracts and full texts were read and refinements to the search were made, a final corpus of 69 publications was analysed using VOSviewer software for text mining and cluster visualisation.

The results highlight how ETs foster the preparedness and resilience of specific systems when dealing with different phases of the DM cycle. Simulation and disaster risk reduction are the fields of major relevance in the application of ETs to DM.

This paper contributes to the literature by adding the lenses of performance measurement, management and accountability in analysing the impact of ETs on DM. It thus represents a starting point for scholars to develop future research on a rapidly and continuously developing topic.

The purpose of this paper is to explain how public sector accounting has changed and is changing due to public governance development.

This paper conducts a traditional literature review based on selected studies in the fields of accounting, public administration and management. The aim of the review is to explain how diverse forms of public governance influence the fate of public sector accounting, including accountability, performance measurement, budgeting and reporting practices.

Public governance is developing into more inclusive but also complex forms, resulting in network, collaborative and digital governance. Consequently, the focus and practices of public sector accounting have changed, as reflected in new types of accountability, performance measurement, budgeting and reporting practices.

Drawing upon literature from different fields enables a deeper understanding of the changes in public sector accounting. Nevertheless, the intention is not to execute a systematic literature review but to provide an overview and resolve the scattered body of knowledge generated by previous contributions. The areas of risk management and auditing were not included and deserve further attention.

This paper discusses the need to continually redefine and reassess public sector accounting practices, by recognising the interdependencies between different actors, citizens and digital technologies.

This paper presents an investigation into the ways the term “practice” is commonly referenced in supply chain management academic papers. Scholars have not yet developed a common understanding of the meaning and do not use practice theories when examining practices related to sustainability management in supply chains. Hence, the authors highlight theoretical gaps and make recommendations for future research.

Grounded in a systematic literature review of 232 peer-reviewed papers published in operations and supply chain management journals, a qualitative content analysis was conducted using both a deductive and an inductive approach.

Results show that supply chain sustainability (SCS) scholars seem barely interested in increasing the understanding of the term “practice,” widely used in the literature to refer to a practical context. Moreover, a clear distinction between being practical and using practice theories to study SCS practices is needed. A descriptive and critical analysis revealed eight key supply chain practices connected to sustainability, with a clear reflection on their meaning. As awareness of practice theories for research on SCS is limited, few recommendations for researchers and practitioners were identified.

Unlike prior literature reviews, the authors reinforce the need to increase the maturity of the SCS field by going beyond superficial theoretical building. Practice theories pathways are provided to enlighten scholars on how to avoid using the term “practice” as taken-for-granted and on how to deal with SCS research and practice.

Mixed methods research is useful to enhance theoretical and practical research contributions. However, single methods have predominated much logistics and supply chain management (LSCM) research. This paper presents a review of mixed methods research across ten years in LSCM to determine their usage, identify benefits and inhibitors, and provide suggestions for LSCM researchers to realise the benefits from using mixed methods.

This paper adopts a mixed methods approach through a quantitative analysis of methods used in six leading LSCM journals, an e-mail survey of mixed methods article authors during the review period, and four published case studies that used mixed methods.

Only 144 (ten percent) of all empirical articles were published using mixed methods during the review period. A range of benefits and inhibitors regarding mixed methods adoption were found. Suggestions for LSCM authors include research training in mixed methods use and developing a project-specific research design due to the specificity and complexity associated with mixed methods research.

LSCM is at a critical juncture, shaped by new contexts, themes and challenges, and would benefit from different research approaches and methods. This paper contributes to the LSCM domain through analysing the current state, benefits and inhibitors of mixed methods research in LSCM journals to provide a renewed call to action and guidelines for mixed methods LSCM research, and suggesting research design adaptation to enable agile and resilient research when investigating rapidly changing and complex phenomena.

The purpose of this study is to empirically test how problem-solving lean practices, along with leaders as learning facilitators in an action learning approach, can be transferred from a production context to a knowledge work context for the purpose of becoming a learning organization while enhancing performance. This is important to study because many organizations struggle to enhance efficiency in the short term while still trying to be long-term learning oriented (i.e. learning organization development).

The authors draw on theory on learning interventions to show how lean practices for problem-solving can foster learning and help an organization to become adaptive. This study’s subject is a non-production department of 100 employees at the LEGO corporation. The authors applied survey results from a natural experiment lasting 18 months between a pre-measurement survey and a post-measurement survey. The results were compared to a control department of 50 employees who were not exposed to the lean practices intervention. The authors’ focus was on the individual level as individuals have different perceptions of lean practices, performance, and learning.

Using repeated-measures tests, difference-in-difference regressions analyses, and structural equation models, the authors find that a package of contemporary lean practices for problem-solving, along with leaders who function as learning facilitators, significantly improved learning organization dimensions while also enhancing efficiency and quality and that learning organizations positively mediate the relationship between the lean intervention and quality-related performance, while efficiency is directly affected by the lean interventions. Data from LEGO's key performance indicators (KPIs), benefit trackers, on-site observations and more than 40 interviews with managers provided results that were consistent with the survey data. A detailed description of the lean practices implemented is provided to inspire future implementations in non-operations environments and to assist educators.

The authors contribute to the learning literature by showing that a learning-to-learn approach to lean management can serve as an active and deliberate intervention in helping an organization becoming a learning organization as perceived by the individual organizational members. The authors also add to the lean literature by showing how a learning approach to lean, as used by LEGO, can positively affect short-term efficiency and quality and create a foundation for a longer-term competitive advantage (i.e. a learning organization) in a non-production context. By contrast, most of the lean literature streams treat efficiency separately from a learning organization and mainly examine lean in a production context.

The extant literature shows three research streams on lean, learning, and performance. The authors built on these streams by trying to emphasize both learning and efficiency. Prior research has not empirically tested whether and how the application of problem-solving lean practices combined with leaders as learning facilitators helps to create a comprehensive learning organization while enhancing performance in a non-production context.

This paper aims to improve our understanding of performance measurement systems in the health and care sector, by focussing on employee reactions to core performance measurement practices. Targets and monitoring are hypothesised to be associated with employee perceptions of job control, supportive management and job demands, which in turn, are expected to be linked to employee-wellbeing and organisational commitment.

Matched employee workplace data are extracted from a nationally representative and publicly available survey. Structural equation models are estimated.

Performance measurement systems are neither perceived as resources nor additional demands. Setting many targets and a focus on productivity can lead to negative employee outcomes, since these positively correlate with perceptions of job demands, which negatively correlate with employee wellbeing. However, monitoring financial performance and monitoring employee performance may be helpful to managers, as these are positively associated with employee perceptions of job control and supportive management, which positively correlate with job satisfaction and organisational commitment and, negatively, with anxiety. Overall, common criticisms of performance measurement systems in healthcare are questioned.

Given the lack of consensus on how performance measurement systems can influence employee experiences and outcomes, this study combines theories that argue for performance measurement systems in managing operations with models developed by psychologists to describe how perceptions of the work conditions can affect employee attitude and wellbeing. A conceptual model is therefore developed and tested, and potential direct and indirect effects of performance measurement systems in the health sector are inferred.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.